Impacts of social and economic factors on the transmission of coronavirus disease (COVID-19) in China
Yun Qiu, Xi Chen, Wei Shi
doi: https://doi.org/10.1101/2020.03.13.20035238
Abstract
This paper examines the role of various socioeconomic factors in mediating the local and cross-city transmissions of the novel coronavirus 2019 (COVID-19) in China. We implement a machine learning approach to select instrumental variables that strongly predict virus transmission among the rich exogenous weather characteristics. Our 2SLS estimates show that the stringent quarantine, massive lockdown and other public health measures imposed in late January significantly reduced the transmission rate of COVID-19. By early February, the virus spread had been contained.
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